What data for this category looks like
Data comes from formula systems, raw material batch records, internal mixers, Mooney viscometers, vulcanizers, and laboratory testing equipment. Updates align with each raw material truck batch, each batch of compounded rubber, and each vulcanized product. Daily documents include formula sheets, weighing and feeding records, mixing torque-temperature curves, rapid rubber property test reports, vulcanization process cards, mold usage records, and finished product performance test reports. Document fields include rubber type ratio, additive dosage, mixing time and temperature, vulcanization holding duration, finished product tensile strength units, and other items. The data structure is dynamically updated alongside production batches.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Frequently updated batch data requires multi-turn dialogue contexts to be accurately bound to the current production batch identifier, to avoid calling expired data. Multiple types of heterogeneous documents (curves, numerical reports, process cards) require prompts to be configured with dedicated parsing rules for different document types. For example, extract torque peak values and temperature ranges from mixing curves, and match holding duration parameters from vulcanization process cards. Fields with units require prompts to enforce verification of matching between numerical values and units, to prevent unit confusion for feeding ratios and temperature parameters. Supplier audits require comparison of multi-dimensional batch data, and multi-turn dialogue must retain context associations to support cross-document batch traceability queries.
How to set the configuration
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId generation rule | Generate a unique ID for each single audit session | Isolate contexts of different supplier audit sessions to prevent data cross-talk |
| Maximum context size | 8000–12000 characters | Match the total character count of multiple documents for mixing and vulcanization batches, to avoid truncation of critical batch data |
| Single search limit | Top 5 entries | Limit the number of returned documents, to align with the number of associated documents for a single batch of mixing and vulcanization |
variables | Bind current batch ID and supplier ID | Accurately locate formula, process, and test data for the corresponding batch, to avoid cross-batch confusion |
messages context retention | First 6 rounds of dialogue | Cover the complete audit workflow from supplier qualification review to batch parameter verification, and retain key question and response contexts |
| Knowledge base reference toggle | Enable on dialogue trigger | Only call knowledge base content for the corresponding batch when a user request matches documents, to avoid interference from irrelevant data |
Three common mistakes
- Phenomenon: The system throws an error when configuring
variablesto pass a knowledge base ID. Cause: The associated format for binding the current batch ID and supplier ID was not followed per category requirements, and passing a standalone knowledge base ID directly caused parameter verification failure. - Phenomenon: Expired mixing curve data is returned during multi-turn dialogue. Cause:
chatIdwas not bound to the current audit session, causing the context to call document data from historical batches. - Phenomenon: The knowledge base returns a large number of irrelevant non-current batch documents. Cause: Knowledge base reference was not configured to trigger on dialogue, and the default full knowledge base content was loaded without batch filtering.
How to confirm the configuration is complete
- Launch a simulated supplier audit dialogue, enter keywords for the current batch's mixing parameters, and verify that returned documents only include associated content for the corresponding batch.
- Review the
variablesparameter binding items, and confirm that identifiers for the current batch ID and supplier ID have been associated. - Test launching two independent audit sessions, and confirm that contexts from different sessions do not interfere with each other.
- Upload a test mixing curve document, and verify that the prompt correctly extracts numerical values and matching items with corresponding units.
The values provided are common starting points and should be measured against the reader's own samples.